Central Limit Theorem in View of Subspace Convex-Cyclic Operators [PDF]
In our work we have defined an operator called subspace convex-cyclic operator. The property of this newly defined operator relates eigenvalues which have eigenvectors of modulus one with kernels of the operator.
H.M. Hasan +3 more
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A comparative evaluation of sufficient dimension reduction and traditional statistical methods for composite biomarker score construction in diagnostic classification [PDF]
Background Combining multiple biomarkers into a single diagnostic score can improve disease classification. However, traditional methods such as logistic regression and linear discriminant analysis depend on restrictive distributional assumptions, which ...
Hulya Ozen, Ertugrul Colak, Dogukan Ozen
doaj +2 more sources
Pattern discovery and subspace clustering play a central role in the biological domain, supporting for instance putative regulatory module discovery from omics data for both descriptive and predictive ends.
Leonardo Alexandre +2 more
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Sufficient Dimension Reduction: An Information-Theoretic Viewpoint
There has been a lot of interest in sufficient dimension reduction (SDR) methodologies, as well as nonlinear extensions in the statistics literature. The SDR methodology has previously been motivated by several considerations: (a) finding data-driven ...
Debashis Ghosh
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Transformed central quantile subspace [PDF]
arXiv admin note: text overlap with arXiv:1906 ...
openaire +2 more sources
Graph adaptive semi-supervised discriminative subspace learning for EEG emotion recognition
Since Electroencephalogram (EEG) is resistant to camouflage and contains abundant neurophysiological information, it shows significant superiorities in objective emotion recognition, making EEG-based emotion recognition become a hot research field in ...
Fengzhe Jin +4 more
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Dimension reduction with expectation of conditional difference measure
In this article, we introduce a flexible model-free approach to sufficient dimension reduction analysis using the expectation of conditional difference measure.
Wenhui Sheng, Qingcong Yuan
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Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions [PDF]
Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data analysis and scientific computing.
Halko, Nathan +2 more
core +6 more sources
A local Wheeler-DeWitt measure for the string landscape
According to the ‘Cosmological Central Dogma’, de Sitter space can be viewed as a quantum mechanical system with a finite number of degrees of freedom, set by the horizon area.
Bjoern Friedrich +4 more
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A Multiple Subspaces-Based Model: Interpreting Urban Functional Regions with Big Geospatial Data
Analyzing the urban spatial structure of a city is a core topic within urban geographical information science that has the ability to assist urban planning, site selection, location recommendation, etc.
Jiawei Zhu +6 more
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